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Koine, Co-Founder, Phil Mochan

The emergence of new digital technology in finance has, somewhat ironically, brought back the terminology of a bygone era. Tokenised value (invariably held on a distributed ledger such as a blockchain) is now kept in “cold storage” (think physical safe), secured by digital keys and transacted by manual processes involving humans and “hot wallets” (think armoured cars).

The nature of digital assets is that the access layer to the value is via a private key, typically a string of alphanumeric characters that can be written down as a piece of paper or saved in a computer file. Digital assets can be compared to a credit card number without a pin or signature being required to authorise expenditure. They are bearer instruments: you hold them, you own them. A familiar bearer instrument is paper money, such as a £10 note. The difference is that the note, whilst having a unique serial number, also has number of additional anti-counterfeit measures. By contrast, the digital asset’s private key has no such measures and can be copied simply by recording it by hand, photographing it or accessing the computer on which it is stored.

Private keys are not only more vulnerable than conventional bearer instruments, such as cash, they also come in a highly portable format. A million pounds in cash will fit in in a modest suitcase. At ten million pounds, it starts to become burdensome and noticeable. By contrast, the same digital asset’s private key can equally hold one pound or a billion pounds, held on a slip of paper in a jacket pocket.

As the value of digital assets has grown exponentially since their emergence in 2008, to a peak of over 700 billion dollars, so has the risk around holding private keys grown dramatically – particularly when funds are exchanged through intermediaries. When paper certificates and cash were used by capital markets to transact 40 years ago, the model involved holding the paper in large physical bank safes and manually removing the transaction amounts using humans to transfer them to armoured trucks with guards.

Not only was this security model rather expensive (armoured vans, steel vaults and lots of people), it was also rather susceptible to internal collusion and theft. As Hollywood has demonstrated with its many heist movies, stealing from armoured trucks and safes is a popular criminal activity, with each subsequent movie seeking to explore a more elaborate and sophisticated way of stealing the money.

There have not yet been mainstream Hollywood movies depicting the opportunity for digital assets (“Bitcoin Big Bang”, a movie on MtGox was a rather niche production), but the press has covered a number of the more spectacular ones. It is estimated that the value of assets stolen in 2019 reached 4.4 billion dollars, up by 260% compared to the previous year (1.7 billion dollars)[1].

With digital assets, such as Bitcoin, hot wallets are the transitory accounts (funded from cold storage) used to settle investors transactions. “Hot” refers to the fact that these accounts are accessible through a public network. Other than that, there is no consistent definition in the industry in terms of the type and strength of controls required (or relaxed) compared to cold wallets. As investors have learned from a long litany of incidents, hot wallets are the preferred target for attacks.

The idea of treating digital assets as physical items reveals the teething issues of these new markets: a digital safe requires humans to interact with value. This renders settlement among market participants risky and inefficient, with many operational limitations.

Faced with similar issues – the risk of handling paper certificates – financial markets developed central securities depositories, institutions that maintain a record of ownership of assets, making the paper certificate irrelevant. The advantage of settling securities in this novel way proved immense: the risk of handling certificates – tangible objects – was eradicated, opening the way to the exponential growth of global securities markets.


The growth of S&P 500 trading volumes over time

Investors in digital assets today are faced with material levels of operational risk, similar to those that forced securities markets to restructure their infrastructure with the dematerialisation of securities.

In the digital assets world, the current poor security model has come into focus in particular from regulators (such as SEC which has blocked insurance of Bitcoin ETF due to lack of effective custody solution) and for institutional capital, which seeks an insured and safe digital asset market which conforms to the expected norms of a trading environment.

Market Infrastructure providers to digital asset markets have been slow in addressing this risk.  Controls over private keys (the physical element kept in hot or cold storage) have been strengthened with elegant technology – better safes, better armoured tracks and more people – but little has been done to tackle the principal issues inherent with the handling of bearer assets. Multi-signature accounts or multi-part computation are often cited as effective solutions. These controls are the digital version of better physical safes or armoured tracks, but they remain ineffective against internal collusion – the primary cause of loss for investors. Furthermore, the manual handling of keys significantly limits scalability and performance of settlement processes.

The cryptocurrency Bitcoin was initially devised to deprive intermediaries of their dominant role in the management and transfer of value yet, ironically, intermediaries are still dominant, they are just new (and probably riskier). The dream of anonymity and disintermediation from centralised trusted parties as imagined by the creators and many supporters of Bitcoin, has given way to hard practicalities of delivering effective security, operational efficiency and meeting the regulatory requirements.

Therefore, in this new environment, centralised trust will continue to be an essential feature to ensure that these new digital markets function efficiently.  Fundamentally it comes down to trust in the custody of assets, when investors are required to delegate its safekeeping to an independent party, and trust in the settlement of transactions, to an agreed set of standards with certainly of timely legal finality.

The digitalisation of assets will in future bring frictionless value transfer and riskless trade matching.  This will evidently require improved conventional market models using dematerialised digital assets, operating with a full separation of duties model, with DvP settlement and using digital CSDs.

Digitalisation will undoubtedly increase the investible universe of assets available to capital (be it property, collateralised debt or digitalised art), increase the accessibility of those assets to a wider range of investors, and create greater fluidity (price transparency, low cost execution and buy-side access) when it comes time to sell.  We can foresee that digital custodians, using dematerialised business models, will grow to become the dominant providers in a rapidly growing market for holding safe, all digital value. This, we believe, will prompt an exponential growth in trading volumes and, particularly in stressed market situations, a considerable reduction in systemic and trading risks.

[1] See CipherTrace report



Mitigating the insurance risks of climate change through geospatial data visualisation




Richard Toomey, Senior Manager, Commercial Insurance at LexisNexis Risk Solutions UK and Ireland


In the lead up to the 26th United Nations Climate Change Conference of the Parties (COP26)[i] November 2021, A United in Science report[ii]  provided a stark warning of the impact and acceleration of climate change. The UK Environment Agency also warned of more extreme weather leading to increased flooding and drought[iii]. While some progress was made at the conference, understanding the changing risks created by extreme weather to price property insurance more effectively, and more importantly, to help mitigate the physical risks posed by climate change, has become imperative.

Mapped geospatial data intelligence including live data on flood warnings and river flows, viewed alongside data held by insurance providers on the properties in their portfolio, can be a key ally in helping to protect customers and reduce claims losses created by extreme weather events.

With the air temperature rising and heavy rain becoming more and more frequent due to climate change insurance providers are looking to identify properties that are more at risk than others. For example, properties with basements carry more of a substantial risk of surface water claims than others and especially in London where space is tight and water runoff is low. In the autumn of 2021, the industry saw a number of high value claims due to basement flooding. There are some really large high net worth (HNW) households with big basements which carry a significant insurance risk.  The problem is that in many cases insurance providers don’t know if they have a property ‘on cover’ that actually has a basement.

The huge and growing volume of data now available to the insurance market to assess property risk to the level the industry needs, could easily overwhelm and prove a barrier to the swift decisions needed in weather-related surge events. However, the evolution of desktop based geospatial data visualisation tools such as LexisNexis® Map View means insurance providers can make quick, informed decisions based on a picture or map of risk, looking at a specific geographical region, a postcode, an address or a single property outline.

They can look at environmental risks including flood, fire and subsidence and live flood data updated every 15 minutes direct from the Environment Agency, as well as highly predictive flood risk data from respected flood modelling organisations. Insurance providers can also bring in data on the characteristics of a property to understand more about its construction, including the type of roof it has, how many floors there are, the square footage, as well as further data on the location and the individuals behind a business to gain a more holistic understanding of risk for pricing.

Mapping of historical flood data brings a further dimension to the understanding of risk, revealing the maximum extent of all individually recorded flood outlines from rivers, the sea and groundwater springs in England and Wales. This takes into account the presence of defences, structures, and other infrastructure where they existed at the time of flooding and includes floods where overtopping, such as at seawalls, river breaches or blockages may have occurred.

But the real step-change for the market has been recent ability to view live flood and other environmental data in tandem with customer and policy data held within an insurance providers’ own databases.

Crucially, this means insurance providers can pinpoint down to individual properties, the policyholders most at risk as weather events unfold, should a river burst its banks, or a flood barrier fail and those properties that may actually be vacant at the time of the event.

Through data visualisation tools, insurance providers can gauge where flood water may go so that policyholders can be warned to take measures to protect themselves, their possessions and to move any vehicles to higher ground. They can even see where roads may have been closed due to fallen trees. All this intelligence helps with planning on the ground resources, working with local authorities and claims adjusters. Then, in the immediate aftermath, rather than wait for a deluge of claims, insurance providers are in a position to reach out to customers known to be in areas affected to support them through the claims process.

The inherent flexibility of today’s geospatial data visualisation tools for the insurance market means risk can be assessed as needed or as constant monitor for a whole commercial property portfolio. Fundamentally these tools are designed to streamline the assessment of property risk.

In the future, commercial and residential property claims data gathered from the whole of the market may allow insurance providers to look at a whole portfolio alongside past claims, but for now they can bring in their own claims data to build a more granular picture of risk, to price more accurately and understand how they could help mitigate future claims and potential losses caused by weather events.

A picture can say a thousand words and data visualisation tools can certainly make highly complex risk data easy to understand and act upon. Being able to instantly visualise an environmental risk to policyholders – day or night – using highly granular data on past and present flood events puts insurance providers in a more powerful position to reduce the misery and costs caused by extreme weather.

[i] https://ukcop26. org/wp-content/uploads/2021/07/COP26-Explained. pdf

[ii] https://public. wmo. int/en/media/press-release/climate-change-and-impacts-accelerate

[iii] https://www. gov. uk/government/news/adapt-or-die-says-environment-agency – The Environment Agency’s third adaptation report October 2021


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What should you be know about PAN data in PCI DSS?




Narendra Sahoo (PCI QSA, PCI QPA, CISSP, CISA, CRISC) is the Founder and Director of VISTA InfoSec



PAN Number or Primary Account Number as we call it is a very sensitive data often used when making online payments or transactions. Customers often share this data with merchants from whom they purchase products or services online. However, customers do expect the merchants and financial institutes to protect the data and prevent incidents of threat. Storing the PAN data for most merchants is a necessity as they may have a legitimate business reason to store cardholder data. But storing PAN data has its share of risk on a business’s network security. Over the years businesses have been storing this data on their server for easy and quick access without realizing the risk it holds and the impact it may have on business.

In fact, most of the data breach incidents that have occurred over the years are due to the storage of unencrypted PAN data on the merchant’s/Service Provider’s servers. While the PCI Council clearly states not to store PAN data yet most merchants for increased consumer convenience store PAN data on their network. Storing customer’s PAN data increases the security risk and, also increases the scope of PCI compliance. So, unless businesses have a legit commercial reason to store PAN data, should not store it. Covering more on this in detail we have today shared details about PAN data and PCI DSS that businesses must know to ensure compliance. So, before getting straight to it let us understand the term PAN Data.


What is PAN Data?

PAN Data is basically the 15 or 16 digit numbers on the front of your debit/credit card which is also known as the Primary Account Number. They are also called payment card numbers and are often found on payment cards like credit and debit cards. The PAN account number is printed or embossed on the front of this payment card. The PAN number is issued by customers to merchants at the Point of Sale (POS) that identifies the issuer and the cardholder account while making payments. Customers when making an online purchase share the PAN number to make payments online. These PAN details are used by the merchants to process the payments online.


How does PAN Impact PCI DSS Compliance?

Payment Card Industry Data Security Standard clearly states that merchants dealing with online payments or accepting credit/debit card payments must avoid storing sensitive PAN numbers. The PCI DSS Requirement 3 addresses the protection of stored cardholder data. So, considering the storage of PAN data will automatically increase the scope of PCI DSS Compliance for the merchants. This way merchants will have to take additional measures for securing the stored PAN data in the network.

Storing unencrypted PAN data on the network will increase the potential risk of breach and end up having a significant impact on business. It is therefore necessary to secure PAN Data in form of encryption or other techniques as suggested in PCI DSS requirements. Explaining the requirement we have shared the PCI DSS data storage requirements in detail.


PAN Data storage in PCI DSS

Merchants may at times for commercial purposes may have to store PAN Data in their server. For these reasons, they will have to take extra precautions and implement additional measures to ensure the security of data and compliance with PCI DSS. The PCI Council outlines the requirement of encryption of cardholder data stored with the merchant. However, it is important to note that not all elements of cardholder need to be encrypted when stored on the server. It is only the PAN data that needs to be encrypted, the rest of the Sensitive Authentication Data (SAD) such as Stripe Data, are not allowed to be even stored by merchants.

What is more important to know and understand about PAN Data storage is that the only times that PAN is not considered to be cardholder data would be when details such as the the cardholder’s name and/or expiry date are not mentioned.  But this does not really happen and so merchants will have to implement measures to secure PAN data. Merchants must equip their data network to deal with PAN securely especially when it is transmitted at the POS.

Moreover, PCI DSS requirement 3.4 states that all merchants must use one of the following techniques to render PAN unreadable. This requirement applies when the PAN Data is stored or when the data is at rest anywhere including portable digital media, backup media, and logs. The techniques of rendering the PAN data unreadable includes

  • Strong cryptography of the PAN
  • PAN truncation (removal of the middle digits),
  • Index tokens and pads
  • Key-management processes

PCI DSS requirement 3.3 specifically requires the PAN data to be masked whenever on display. So, this way, the only digits of the PAN that may be visible are the first six and last four digits. With this only authorized businesses with legitimate commercial needs can see the rest of the information.


Final Thought

Despite all the clarity given in terms of the possible threat with storing PAN data nearly 65% of the merchants continue to store unencrypted PAN data on their servers and network. Further, what adds to the problem is that merchants are not able to handle and appropriately secure these stored PAN and cardholder data. Understanding the importance of PAN data and securing them is crucial. This is to prevent incidents of breach and theft. So, the only possible way to prevent this is by implementing measures of defense for handling such sensitive data. Ensuring that the PAN is  protected using one-way hashing or truncation methodologies is one way of assuring the customer’s security of the cardholder data. This way it would also help businesses ensure maintaining PCI DSS Compliance and securing sensitive data.

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